Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals two important behaviors: matching uses 'any of' semantics (OR-style filtering) and rows are returned 'in the order given.' It does not describe the output format or side-by-side presentation, but the core behavior is clearly communicated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, tightly worded sentence with no filler. It front-loads the main behavior and appends the usage qualifier efficiently.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a two-parameter read-style tool, the description tells an agent what to pass and what to expect in terms of selection and ordering. It does not specify the exact return shape, but the absence of an output schema is partially mitigated by the straightforward nature of the operation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must define the parameters, and it does: 'column' is the field being matched and 'values' are the accepted values, with 'any of' clarifying the matching semantics. This adds genuine meaning beyond the plain schema types, though it leaves maxItems/minItems details to the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly specifies that the tool returns rows from the Scopedly dataset filtered by whether a column matches any provided values. The 'for "X vs Y" questions' qualifier gives it a distinct identity among the sibling data tools, though it does not explicitly contrast itself with dataset_row or dataset_search.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'for "X vs Y" questions' provides a clear usage context: this tool is for comparing sets of values in a column. It does not, however, explicitly state when not to use it or name alternative sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.